Common variants in Mendelian kidney disease genes and their association with renal function.

Many common genetic variants identified by genome-wide association studies for complex traits map to genes previously linked to rare inherited Mendelian disorders. A systematic analysis of common single-nucleotide polymorphisms (SNPs) in genes responsible for Mendelian diseases with kidney phenotypes has not been performed. We thus developed a comprehensive database of genes for Mendelian kidney conditions and evaluated the association between common genetic variants within these genes and kidney function in the general population. Using the Online Mendelian Inheritance in Man database, we identified 731 unique disease entries related to specific renal search terms and confirmed a kidney phenotype in 218 of these entries, corresponding to mutations in 258 genes. We interrogated common SNPs (minor allele frequency >5%) within these genes for association with the estimated GFR in 74,354 European-ancestry participants from the CKDGen Consortium. However, the top four candidate SNPs (rs6433115 at LRP2, rs1050700 at TSC1, rs249942 at PALB2, and rs9827843 at ROBO2) did not achieve significance in a stage 2 meta-analysis performed in 56,246 additional independent individuals, indicating that these common SNPs are not associated with estimated GFR. The effect of less common or rare variants in these genes on kidney function in the general population and disease-specific cohorts requires further research.

Genome-wide association analyses identify 18 new loci associated with serum urate concentrations.

Elevated serum urate concentrations can cause gout, a prevalent and painful inflammatory arthritis. By combining data from >140,000 individuals of European ancestry within the Global Urate Genetics Consortium (GUGC), we identified and replicated 28 genome-wide significant loci in association with serum urate concentrations (18 new regions in or near TRIM46, INHBB, SFMBT1, TMEM171, VEGFA, BAZ1B, PRKAG2, STC1, HNF4G, A1CF, ATXN2, UBE2Q2, IGF1R, NFAT5, MAF, HLF, ACVR1B-ACVRL1 and B3GNT4). Associations for many of the loci were of similar magnitude in individuals of non-European ancestry. We further characterized these loci for associations with gout, transcript expression and the fractional excretion of urate. Network analyses implicate the inhibins-activins signaling pathways and glucose metabolism in systemic urate control. New candidate genes for serum urate concentration highlight the importance of metabolic control of urate production and excretion, which may have implications for the treatment and prevention of gout.

Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function.

In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10(-9)) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10(-4)-2.2 × 10(-7). Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in general.

Genome-wide association and functional follow-up reveals new loci for kidney function.

Chronic kidney disease (CKD) is an important public health problem with a genetic component. We performed genome-wide association studies in up to 130,600 European ancestry participants overall, and stratified for key CKD risk factors. We uncovered 6 new loci in association with estimated glomerular filtration rate (eGFR), the primary clinical measure of CKD, in or near MPPED2, DDX1, SLC47A1, CDK12, CASP9, and INO80. Morpholino knockdown of mpped2 and casp9 in zebrafish embryos revealed podocyte and tubular abnormalities with altered dextran clearance, suggesting a role for these genes in renal function. By providing new insights into genes that regulate renal function, these results could further our understanding of the pathogenesis of CKD.

Quantitative phosphokinome analysis of the Met pathway activated by the invasin internalin B from Listeria monocytogenes.

Stimulated by its physiological ligand, hepatocyte growth factor, the transmembrane receptor tyrosine kinase Met activates a signaling machinery that leads to mitogenic, motogenic, and morphogenic responses. Remarkably, the food-borne human pathogen Listeria monocytogenes also promotes autophosphorylation of Met through its virulence factor internalin B (InlB) and subsequently exploits Met signaling to induce phagocytosis into a broad range of host cells. Although the interaction between InlB and Met has been studied in detail, the signaling specificity of components involved in InlB-triggered cellular responses remains poorly characterized. The analysis of regulated phosphorylation events on protein kinases is therefore of particular relevance, although this could not as yet be characterized systematically by proteomics. Here, we implemented a new pyridopyrimidine-based strategy that enabled the efficient capture of a considerable subset of the human kinome in a robust one-step affinity chromatographic procedure. Additionally, and to gain functional insights into the InlB/Met-induced bacterial invasion process, a quantitative survey of the phosphorylation pattern of these protein kinases was accomplished. In total, the experimental design of this study comprises affinity chromatographic procedures for the systematic enrichment of kinases, as well as phosphopeptides; the quantification of all peptides based on the iTRAQ reporter system; and a rational statistical strategy to evaluate the quality of phosphosite regulations. With this improved chemical proteomics strategy, we determined and relatively quantified 143 phosphorylation sites detected on 94 human protein kinases. Interestingly, InlB-mediated signaling shows striking similarities compared with the natural ligand hepatocyte growth factor that was intensively studied in the past. In addition, this systematic approach suggests a new subset of protein kinases including Nek9, which are differentially phosphorylated after short time (4-min) treatment of cells with the Met-activating InlB(321). Thus, this quantitative phosphokinome study suggests a general, hypothesis-free concept for the detection of dynamically regulated protein kinases as novel signaling components involved in host-pathogen interactions.

A protein database constructed from low-coverage genomic sequence of Bacillus megaterium and its use for accelerated proteomic analysis.

Peptide mass fingerprint (PMF) matching is a high-throughput method used for protein spot identification in connection with two-dimensional gel electrophoresis (2DE). However, the success of PMF matching largely depends on whether the proteins to be identified exist in the database searched. Consequently, it is often necessary to apply other more sophisticated but also time-consuming technologies to generate sequence-tags for definitive protein identification. On the other hand, modern sequencing technologies are generating a large quantity of DNA sequences, first in unfinished form or with low genome coverage due to the time-consuming and thus limiting steps of finishing and annotation. We recently started to sequence the genome of Bacillus megaterium DSM 319, a bacterium of industrial interest. In this study, we demonstrate that a protein database generated from merely three-fold coverage, unfinished genomic sequences of this bacterium allows a fast and reliable protein spot identification solely based on PMF from high-throughput MALDI-TOF MS analysis. We further show that the strain-specific protein database from low coverage genomic sequence greatly outperforms the commonly used cross-species databases constructed from 13 completely sequenced Bacillus strains for protein spot identification via PMF.

JVirGel: Calculation of virtual two-dimensional protein gels.

We developed JVirGel, a collection of tools for the simulation and analysis of proteomics data. The software creates and visualizes virtual two-dimensional (2D) protein gels based on the migration behaviour of proteins in dependence of their theoretical molecular weights in combination with their calculated isoelectric points. The utilization of all proteins of an organism of interest deduced from genes of the corresponding genome project in combination with the elimination of obvious membrane proteins permits the creation of an optimized calculated proteome map. The electrophoretic separation behaviour of single proteins is accessible interactively in a Java(TM) applet (small application in a web browser) by selecting a pI/MW range and an electrophoretic timescale of interest. The calculated pattern of protein spots helps to identify unknown proteins and to localize known proteins during experimental proteomics approaches. Differences between the experimentally observed and the calculated migration behaviour of certain proteins provide first indications for potential protein modification events. When possible, the protein spots are directly linked via a mouse click to the public databases SWISS-PROT and PRODORIC. Additionally, we provide tools for the serial calculation and visualization of specific protein properties like pH dependent charge curves and hydrophobicity profiles. These values are helpful for the rational establishment of protein purification procedures. The proteomics tools are available on the World Wide Web at http://prodoric.tu-bs.de/proteomics.php.